code: def u(self):
      u_unnormed = (
          self.u_unnormed()
          if callable(self.u_unnormed)
          else self.u_unnormed
      )
      norm = torch.norm(u_unnormed, p=2, dim=-1, keepdim=True)
      return torch.div(u_unnormed, norm)
  
imports: import math
  import warnings
  from functools import partial
  import torch
  import torch.nn
  from torch.distributions import Transform, constraints
  from pyro.nn import DenseNN
  from ..conditional import ConditionalTransformModule
  from ..torch_transform import TransformModule
  from ..util import copy_docs_from
label_desc: Use image node_id 2 for calling the ConditionedHouseholder obj's underlying member method code with example usage: obj.u() and returns: torch